Snow Cover Mapping Based on SNPP-VIIRS Day/Night Band: A Case Study in Xinjiang, China

Detailed snow cover maps are essential for estimating the earth’s energy balance and hydrological cycle. Mapping across spatially extensive topographically complex areas with less or no cloud obscuration is challenging, but SNPP-VIIRS Day/Night Band (DNB) nighttime light data offers a potential solution. This paper aims to map distribution at 750 m resolution diverse 1,664,900 km2 of Xinjiang, China, based on DNB radiance. We implemented swarm intelligent optimization technique Krill Herd algorithm, which finds optimal threshold value by taking Otsu’s method as objective function. derived 14 consecutive scenes in December 2021, compared our snow-covered area estimations those from MODIS AMSR2 standard products, generated composite merging data. Results show that capable providing reliable superior AMSR2, an overall accuracy level 84.66%. The 500 spatial provided 55.85% more information than products achieved 84.69%. Our study demonstrated feasibility detection Xinjiang DNB, can serve supplementary dataset where clouded pixels present.